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Related Concept Videos

Tactile and Chemical Senses01:27

Tactile and Chemical Senses

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Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex.
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Somatosensation01:33

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The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.
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Related Experiment Video

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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Haptic Exploration of Unknown Objects for Robust In-Hand Manipulation.

Gokhan Solak, Lorenzo Jamone

    IEEE Transactions on Haptics
    |August 1, 2023
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    This study introduces a robot hand manipulation framework that uses haptic exploration to learn object properties and motion. This method significantly improves manipulation accuracy and robustness for unknown objects in unstructured environments.

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    Area of Science:

    • Robotics
    • Artificial Intelligence
    • Haptics

    Background:

    • Robotic manipulation in unstructured environments requires knowledge of object properties and motion, which is often unavailable.
    • Grasping unknown objects without prior information leads to poor manipulation stability, accuracy, and repeatability.
    • Efficiently acquiring object information is a key challenge for in-hand manipulation.

    Purpose of the Study:

    • To develop an in-hand manipulation framework for unknown objects without prior information.
    • To extract object properties using a novel haptic exploration procedure.
    • To learn object motion from demonstration using dynamical movement primitives.

    Main Methods:

    • A human-like robot hand was used for in-hand manipulation experiments.
    • A novel haptic exploration procedure was employed to gather object property data.
    • Dynamical movement primitives were utilized for learning manipulation trajectories from demonstrations.

    Main Results:

    • The proposed framework successfully manipulated unknown objects.
    • Haptic exploration significantly enhanced manipulation robustness and accuracy.
    • Performance was compared against the widely used virtual spring framework baseline.

    Conclusions:

    • Haptic exploration is an effective method for acquiring object properties in robotic manipulation.
    • The developed framework improves the performance of in-hand manipulation for unknown objects.
    • This approach offers a pathway for more adaptable and precise robotic manipulation in real-world scenarios.